• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.4
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• pp.342-347
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• 2008

Mortality and growth rate of the soft coral, Dendronephthya gigantea, from Jejudo Island on the southern coast of Korea were investigated from February 2003 to October 2004 using SCUBA diving. 48 individuals with variable sizes of D. gigantea of the depth of 15m were tagged with flagging tapes and plastic films, and then monitored with two month intervals. The average mortality of two-month term for the study period was 50.4%, with the peak of 84.6% during the summer storms in August - October 2003. About the size class mortality, individuals of size class I(${\leq}$10 cm) showed the highest mortality, followed by size class III(>20 cm) and size class II(10 cm-20 cm). Growth rate did not show a seasonal pattern. For growth in length, individuals of D. gigantea grew about 3cm in average for two-month period, with a maximum growth of 6.4 cm which occurred in August - October 2003. For growth in diameter, individuals grew about 0.3 cm for 2 month term, with a maximum of 1.4cm in April - June 2004. Individuals of size class I usually grew faster than those of larger size classes. D. gigantea population in Jejudo Island was strongly affected by summer storms, which was due to annual event of summer typhoon. Never the less, it appears that the local population can be maintained by fast growth of the juvenile stage and active recruitment to compensate the high mortality caused by the summer disturbance.

• Journal of Life Science
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• v.22 no.5
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• pp.642-649
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• 2012

The southern coast of Korea is important for the ark shell ($Scapharca$ $broughtonii$) aquaculture, but the productivity was rapidly reduced during the previous decade by mass mortality. To overcome this economic loss, investigations only focused on environmental factors, and microbiological researches were performed insufficiently. In this study, two sites (Gangjin and Jinhae bay) were selected for their high and low rate of mortality, respectively, and the existence of microflora from underwater sediments in the bodies of $S.$ $broughtonii$ was analyzed. We screened the whole body of each sample and chose unique colonies, which exhibit alpha- and beta-hemolytic activity, for identification. The microflora in $S.$ $broughtonii$ was less variable than sediments, and restricted species were isolated. We identified 17 genera of 88 species and 16 genera of 64 species from the two bays, respectively. A major proportion was comprised of $Bacillus$ species, with the $Bacillus$ $cereus$ group being the most common species among the $Bacillus$ strains, while $Paenibacillus$, $Lynsilbacillus$, and $Vibrio$ species were the second most abundant species. At the genus level, there were no significant microbial differences between the two coastal regions. 64 species were isolated from rare site (Jinhae bay), but more species (88) with greater variety were isolated from the frequent site (Gangjin bay). Therefore, it was assumed that the cause of mass mortality lay in the difference in specie-level diversity, and conducting investigations on the diagnosis of pathogenic species by challenging tests using isolated unique species.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.165-182
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• 1998

When tour site is being used by people for the destination of tour, it has a life, or it will lose its life as a tour site. Therefore this paper aims to, based on Butler's theory, has chosen 46 hot spring spots in Korea which are legally assigned and presently running, and tried to analyze the life cycles, the stage of dispositional characteristics, and visitors' favoritism, and to try to find activating method which is not decline. Out of 46 spots, 29 Places were found on the stage of development, which took high percentage, 4 were on the growing stage, 5 were on the mature stage, 5 were on the stagnation or decline stage and the rest 3 were on the stage of rejuvenation. Geographically, Korean hot springs were located on the plain or mountainous areas mostly, and less of them were on hills and coast lines. In water quality, most of places had simple water while the places with salt and sulfur contained water were marked low rate. The temperatures of hot spring water were variable between $25^{\circ}C{\sim}78^{\circ}C$, but the older hot springs were hotter than new ones. After observing the relationship between disposition characteristics and life cycles, the geographical locations and the matter of approach were found as majour influential factors to the life cycles of them. The type of mountainous areas were observed slow progress in life cycle, due to traffic problem, until the road expansion or pavement work were done. Meanwhile, the suburban ones adjacent to big cities were favored by hot spring tourists due to their easy approach and easy traffic. The new born hot springs with such conditions have shown the fast growth. As studied above, since the hot springs were supposed to be for recuperation and vacational, a hot spring with better recreational and accommodational facilities was more favored by tourists than the one with pretty interior decorations. It was because the tour purpose of people has been switched from single purpose to multi one. Thus, the suggestion for activating a declining hot spring and bringing people in them is to develop new and attractive tour resources, expanding the related area, maintaining good quality of water, developing a complex site for long-term tour, developed traffic routs, hot spring festivals, utilizing adjacent tour resources, preparing public water supply system, and assigning as special tour zone.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.604-617
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• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.8 no.2
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• pp.47-60
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• 1975

For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.